Science topic

Logistics - Science topic

Logistics is the management of the flow of resources, between the point of origin and the point of destination in order to meet the requirements of customers or corporations.
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Hello,my name is Chaimae and my thesis topic is as follow: Management of large distribution logistics in Morocco.
Please tell me what do you think about this subject, wheter it is relevent and original and wether scientific reaserch has sufficiently addressed it. I need youd advices.
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Thank you
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This is my thesis topic:Management of logistics in the large distribution sector in Morocco.
And Here is my prob.: To what extent do the operational strategies developed and policies adopted by promoters of large distribution in Morocco allow for competitively managing the logistics chain of large distribution?
And here are the given hypotheses:
• Hypothesis 1: Close collaboration with suppliers could secure supplies, resolve the plethora of supply chains, guarantee merchandise returns, and professionalize logistics personnel.
• Hypothesis 2: Investing in human resources could enhance the distribution chain's supply, storage performance, order preparation, and shipment, fostering staff loyalty and better customer service.
• Hypothesis 3: Inadequate stock positioning in the logistics chain, improper facility localization, and their inflexibility to support a wide range of products and varying volumes might be the cause of the lack of competitiveness among large distribution companies.
• Hypothesis 4: Poor stock management could be the reason behind high logistics costs in large distribution.
• Hypothesis 5: Poor order preparation and shipment conditions might be among the main causes of mismanaging the customer experience.
What do you think? Your comments? Is this a genuine issue? What could I add or remove?"
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thank you so much
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Hegel's Science of Logic involves a trinary process: understanding -> dialectical reasoning -> speculative reasoning -> understanding at a higher level. This is analogous to a period 3 orbit, a return to self mediated by the other A -> B -> C -> A.
A direct consequence of a really strange theorem in dynamical systems due to Sharkovskii is that for any continuous function on the reals f: R -> R, if f has an orbit of minimal period 3 then it has orbits of any minimal period (because 3 is the first number in the Sharkovskii ordering). This happens in particular for certain values of lambda for the logistic map, exhibiting the phenomenon of 'chaos'.
The graph of successive higher iterations of the logistic map exhibit self-similarity, a fractal-like nature. This again mirrors the structure of the logic in which each part is similar in its trinary structure to that of the whole, i.e. Being -> Essence -> Notion, but in Being we have Quantity -> Quality -> Measure. In Concept we have Subjective Notion -> Objective Notion -> Absolute Notion. At a further finer level inside Quantity we have for instance Pure Being -> Nothing -> Becoming, etc.
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In Hegel's "Science of Logic," the trinary process involves understanding -> dialectical reasoning -> speculative reasoning -> understanding at a higher level. This is analogous to a period 3 orbit, a return to self mediated by the other A -> B -> C -> A.
A direct consequence of a peculiar theorem in dynamical systems by Sharkovskii is that for any continuous function on the reals f: R -> R, if f has an orbit of minimal period 3, then it has orbits of any minimal period (because 3 is the first number in the Sharkovskii ordering). This occurs particularly for certain values of lambda for the logistic map, exhibiting the phenomenon of 'chaos.'
The graph of successive higher iterations of the logistic map exhibits self-similarity, a fractal-like nature. This again mirrors the structure of logic where each part is similar in its trinary structure to that of the whole, i.e., Being -> Essence -> Notion. In Being, we have Quantity -> Quality -> Measure. In Concept, we have Subjective Notion -> Objective Notion -> Absolute Notion. At a finer level inside Quantity, we have, for instance, Pure Being -> Nothing -> Becoming, etc.
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The results of my logistic analysis research show that the pseudo rsquare is only 0.07. Can I still continue my research?
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technically, this should make sense if you compare two R-squared values of the same type (of either linear regression or logistic regression models, however, different models) on the same dataset, predicting the same outcome ...
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Hi, I'm doing scientific research about "The impacts of green logistics performance on economic growth: Evidence from China". This is my first time doing research, so my idea gets troubles a lot, I want to ask you guys some questions.
Firstly, about my idea, I am having problems collecting logistics activities data. I don't know whether the data I collect is in a country that has applied green logistics or not because it is only written as "logistic performance index".
Secondly, my instructor wondered why I chose China (in my opinion, because China emits a lot of CO2 so it will be easy to evaluate the impact of applying green logistics on the economy), but she told me that it is not the case, so I have to consider about it again.
It would be great if you could answer ( any websites to collect data..) and give me directions for this idea, I'm a freshman in this field :(. Thank you so much
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That is a really interesting question and i tries to work on a similar product based problem during my bachelors and here is just an opinion based on my experience-
1) You need to divide the emissions on the basis of Scope 1,Scope 2 and Scope 3 and if we think of this problem not as a logistic proboems but as a supply chain problem.
2) The data for scope 3 emissions firstly is not available, secondly the available one is not reliable, this is the main problem.
3) Even though scope 3 emissions data is not available as a single entity but now lets divide it into categories - air, water and land. Now try to find a country which uses air as its major form of transportation and not water or land because emissions from air logistics can still be tracked and accuntable data can be found, then maybe using that data to somehow figure how much other modes are emitting.
Now the reason why i am suggesting this - Even though countries like China and India emit a lot but remember that these are energy and manufacturing emissions, logistics emissions are extremely small as these countries have already adapted to railwasy which in the case of india are running on 97% electricity only (green logisticcs) and railways accounts for a major chunk of logistics) and compare this with a country like Green land where the only reliable mode of transportation is planes.
I hope i was able to help you
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How do limiting factors determine the carrying capacity of an ecosystem and how does carrying capacity relate to logistic growth?
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Carrying capacity, or the maximum number of individuals that an environment can sustain over time without destroying or degrading the environment, is determined by a few key factors: food availability, water, and space. An ecosystem can support a certain number of organisms depending on the availability of food, shelter, and water. If an ecosystem has more organisms than its water supply can support then it is beyond its carrying capacity. Carrying capacity can be defined as a species' average population size in a particular habitat. The species population size is limited by environmental factors like adequate food, shelter, water, and mates. If these needs are not met, the population will decrease until the resource rebounds.The carrying capacity is the concept that resources are always limited because the environment can only support a certain number of individuals in a population. The logistic growth curve is S-shaped to represent the gradual growth stage, then the rapid growth phase, followed by the slow growth rate at the end. Carrying capacity can be defined as a species' average population size in a particular habitat. The species population size is limited by environmental factors like adequate food, shelter, water, and mates. If these needs are not met, the population will decrease until the resource rebounds.Carrying capacity is an indicator that helps ecologists analyze the availability of resources and predict future population trends. To answer how carrying capacity affects the size of a population, an ecologist would need to know the age structure of the species population. So, in the context of sustainability, carrying capacity is the size of the population that can be supported indefinitely upon the available resources and services of supporting natural, social, human, and built capital. Limiting factors within every ecosystem, such as the availability of food or the effects of predation and disease, prevent a population from becoming too large. These limiting factors determine an ecosystem's carrying capacity, or maximum population size the environment can support given all available resources. Carrying capacity, or the maximum number of individuals that an environment can sustain over time without destroying or degrading the environment, is determined by a few key factors: food availability, water, and space.
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Como se maneja la big data en el proceso logistico en una organizacion, cuales son los avances de los ultimos años
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If you ask chatGPT "How is big data managed in the logistics process within an organization, and what are the recent advances?" a reasonable answer comes up:
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Managing big data in the logistics process within an organization has become increasingly critical in recent years. Here are some of the recent advances in this field:
1. **Real-time Data Analysis:** Logistics companies are now using big data analytics to process and analyze data in real-time. This allows them to make decisions quickly, optimize routes, and respond to changing conditions on the fly.
2. **Predictive Analytics:** Advanced algorithms and machine learning models are being used to predict future logistics trends, demand patterns, and potential disruptions. This helps in proactive decision-making and resource allocation.
3. **IoT Integration:** Internet of Things (IoT) devices, such as GPS trackers and sensors, are extensively used to collect data from vehicles, products, and facilities. This data is then integrated into big data systems to provide a holistic view of the supply chain.
4. **Blockchain Technology:** Blockchain is being explored for enhancing transparency and security in logistics. It helps in tracking goods through the supply chain, reducing fraud, and ensuring data integrity.
5. **Automation and Robotics:** Automation and robotics are increasingly used in warehouses and distribution centers. These technologies generate large amounts of data that can be harnessed for optimization and efficiency.
6. **Cloud Computing:** The adoption of cloud-based solutions has made it easier for organizations to store and process vast amounts of data. This scalability is essential for handling big data effectively.
7. **Data Visualization Tools:** User-friendly data visualization tools make it easier for logistics professionals to interpret and gain insights from big data, facilitating better decision-making.
8. **Environmental Considerations:** Logistics companies are using big data to optimize routes and reduce the environmental footprint by minimizing fuel consumption and emissions.
9. **Supplier and Inventory Management:** Big data analytics help in improving supplier relationships and optimizing inventory levels, reducing costs, and ensuring products are available when needed.
10. **Customization and Personalization:** Big data allows logistics companies to tailor services and products to individual customer preferences, providing a more personalized and efficient experience.
In summary, the management of big data in the logistics process has seen significant advancements in recent years, contributing to more efficient and responsive supply chains, cost reductions, and improved customer experiences. The ability to collect, process, and analyze data has become a crucial competitive advantage in the logistics industry.
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I would add that the biggest problems that companies face is attempting to exploit recent advances is lack of software development skills. The reason is as follows:
1. To exploit new technology the skill must be there to create a test and verify the benefit of the advancement.
2. To test a technology that requires big data as input, big data administration skills are a prerequisite.
3. As these skills are novel (big data is only 10 years old) organisations don't hire enough SW engineers to enable or managing experiments at this scale.
So what are these skills? Again ChatGPT provides a reasonable answer:
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Managing big data effectively requires a combination of technical, analytical, and business skills. Here are some of the key skills required to manage big data:
1. **Data Analysis:** Proficiency in data analysis is crucial. You should be able to extract meaningful insights from large datasets. Familiarity with tools like Python, R, and data analysis libraries is essential.
2. **Data Management:** Understanding data storage and management systems is vital. This includes knowledge of relational databases, NoSQL databases, and data warehousing solutions.
3. **Programming Skills:** Proficiency in programming languages, particularly Python and Java, is important for data manipulation, transformation, and analysis. Knowledge of SQL for database querying is also valuable.
4. **Big Data Technologies:** Familiarity with big data technologies such as Hadoop, Spark, and related ecosystems is essential. These tools enable the processing and analysis of large datasets.
5. **Machine Learning:** Basic understanding of machine learning is beneficial, as it can be applied to extract predictive insights from big data. Knowing how to use machine learning libraries and frameworks is an advantage.
6. **Data Visualization:** The ability to create meaningful visualizations using tools like Tableau, Power BI, or open-source options is crucial for conveying insights to non-technical stakeholders.
7. **Statistics:** A good grasp of statistical methods is essential for data analysis and interpretation. Knowledge of descriptive statistics, inferential statistics, and hypothesis testing is valuable.
8. **Business Acumen:** Understanding the business context is critical. Being able to translate data insights into actionable strategies and decisions that benefit the organization is a key skill.
9. **Data Security and Compliance:** Knowledge of data security best practices and compliance regulations is important, especially when handling sensitive or regulated data.
10. **Problem-Solving:** Strong problem-solving skills are required to address data-related challenges, such as data quality issues, scalability, and performance optimization.
11. **Communication:** Effective communication is crucial for conveying complex technical findings to non-technical stakeholders and decision-makers.
12. **Project Management:** Being able to manage big data projects, including setting objectives, timelines, and resources, is important for successful data management.
13. **Data Engineering:** Understanding data engineering concepts, including data pipelines, data cleansing, and ETL (Extract, Transform, Load) processes, is essential for data preparation and transformation.
14. **Cloud Computing:** Familiarity with cloud platforms like AWS, Azure, or Google Cloud is valuable, as many big data solutions are hosted in the cloud.
15. **Continuous Learning:** Given the rapidly evolving nature of data technologies, a willingness to continually learn and adapt to new tools and techniques is essential.
In summary, managing big data requires a combination of technical, analytical, and business skills. As the field continues to evolve, staying updated with the latest developments and tools is essential to be an effective big data manager.
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Whilst chatGPT lists all the general issues, it is important to recognize that reducing the number of technologies will significantly reduce the cognitive burden of the big data team. Unfortunately, and due to the rapid development of technologies navigating all the possible technologies leads to a jungle of options, where selection of tools for "big data" projects becomes critical. Statistics by Alex Yu (ByteByteGo) reveal that more than 50% of big data projects fail to meet expectations due to wrong choice of technology (e.g. poor tech stack choice) and hence require some form of re-engineering that causes project overrun.
In summary, the lack of skills and previous experiences leaves big data projects to the largest corporations which can afford the learning process.
Finally I recommend you to ask yourself: What makes big data "big"?
A sufficiently technical answer to that question will leave you informed about what is required to manage "big data" and subsequently "how to manage" to prerequisites.
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As we look towards a more sustainable and ethical future, one of the most exciting developments in the world of food is cultivated meat. 🌎🍖
🔬 What is Cultivated Meat? Cultivated meat, also known as lab-grown or cell-based meat, is produced by culturing animal cells in a controlled environment, without the need to raise and slaughter animals. It offers the promise of a more sustainable, humane, and environmentally friendly way to meet our growing global demand for meat.
🌍 Why is it Important?
  • Sustainability: Did you know that the meat industry contributes to approximately 15% of global greenhouse gas emissions annually? As meat consumption continues to rise, so does its impact on the environment. Cultivated meat requires significantly fewer resources, such as land and water, and produces up to 90% less greenhouse gas emissions compared to traditional livestock farming.
  • Animal Welfare: It eliminates the need for factory farming, where millions of animals endure harsh conditions. By embracing cultivated meat, we can reduce animal suffering on an unprecedented scale.
  • Food Security: With the world's population expected to reach 9 billion by 2050, meat consumption is projected to double. Cultivated meat could play a crucial role in ensuring food security while reducing the pressure on our planet's resources.
💲 Price Comparison: Currently, cultivated meat is more expensive to produce than conventionally farmed meat, with prices ranging from approximately $50 to $150 per kilogram. In contrast, the cost of traditional meat production can vary widely but is generally lower.
📈 Future Price Trends: The future of cultivated meat pricing is promising. As technology advances and economies of scale come into play, we can expect the price of cultivated meat to decrease significantly. Projections indicate that it could become cost-competitive with traditional meat within the next decade, making it a viable and sustainable choice for consumers worldwide.
🌟 Engineering Challenges: The development of cultivated meat involves intricate engineering challenges:
  • Bioreactor Design: Creating efficient bioreactors for cell culturing and growth is crucial. Engineers are working on scalable designs to optimize cell proliferation.
  • Nutrient Formulation: Designing the perfect nutrient solution to support cell growth, mimicking the natural environment, is a complex task.
  • Scaffold Materials: Innovations in scaffold materials are vital for replicating the texture of traditional meat.
  • Scaling Production: Transitioning from lab-scale production to large-scale manufacturing presents logistical and technical hurdles.
🧪 Scientific Advancements:
  • Cell Lines: Scientists are continually improving cell lines to enhance flavor and texture, ensuring cultivated meat is indistinguishable from conventionally farmed meat.
  • Culturing Techniques: Developing advanced culturing techniques like 3D bioprinting for complex meat structures is a priority.
  • Sustainability Metrics: Research is ongoing to quantify the precise environmental benefits of cultivated meat production.
💡 Let's Collaborate: I believe in the power of innovation to shape a better future. Whether you're a scientist, entrepreneur, or simply curious about the future of food, let's connect and discuss how we can contribute to this exciting journey.
🌱 Let's Keep the Conversation Going: The potential benefits of cultivated meat are vast, from reducing greenhouse gas emissions to safeguarding our planet's ecosystems. Share your thoughts on these environmental impacts and the groundbreaking technology of cultivated meat in the comments below!
#CultivatedMeat #Sustainability #FutureOfFood #Innovation #FoodTech #EngineeringChallenges #MeatPrices
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Thanks Robert for your thoughtful response. You've brought up some valid points that highlight the complexity of assessing the environmental and ethical aspects of cultivated meat production. Let's address your concerns one by one:
  1. Carbon Emissions from Reagents: You're absolutely right that the carbon emissions associated with the production of cell culture reagents, which are derived from the petrochemical industry, should be considered when evaluating the overall environmental impact of cultivated meat. It's essential to have a comprehensive life-cycle analysis that takes into account all such factors for a more accurate assessment.
  2. Methane vs. CO2 Emissions: The comparison between methane and carbon dioxide emissions is a crucial one, and you rightly point out that reducing methane emissions from livestock is a viable strategy. This is especially true for ruminant animals like cows. However, cultivated meat still has the potential to significantly reduce the overall greenhouse gas emissions compared to traditional livestock farming, even when considering changes in livestock farming practices.
  3. Resource Use for Cultured Meat: It's important to recognize that, as of now, some resource inputs are still required for cultivated meat production, such as the cultivation of cells and the production of growth media. While it may not be a perfect solution, the potential for more efficient resource use and lower environmental impact is significant. The goal is to continually improve and optimize these processes to minimize their impact.
  4. Animal Welfare: You rightly mention that animal welfare concerns are often more about the methods used in the production chain rather than the process itself. However, cultivated meat, by eliminating the need for raising and slaughtering animals on a large scale, can still have a positive impact on reducing animal suffering and addressing welfare issues inherent in traditional livestock farming.
It's essential to acknowledge that cultivated meat is not a perfect solution, and there are challenges and limitations that need to be addressed. It's a rapidly evolving field, and ongoing research and innovation are critical to overcome these challenges and make cultivated meat a more sustainable and ethical alternative to conventional meat production. Collaboration among scientists, entrepreneurs, and interested individuals, as you've suggested, is vital to finding solutions and continuously improving this exciting technology for a better future.
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How can data science and statistical analysis be used to improve the shipping and logistics industry?
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Just like any industry there should be national or state-based reports, as per hospital industry has hospital admissions data in the AIHW reports, there should be a like document for shipping related to statistics collected ie no of ships docked, containers unloaded, weight of shipping containers, products dumped due to contamination etc.
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I have measured Irisin levels in plasma and now I'm trying to analyze the results. As far as I have read, I need to perform a 4 parameter logistic regression, should I use logarithm for absorbances and for concentrations?
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I use the program Prism GraphPad for that. The data used is only the concentration level of the standard curve and the optical density levels. Then I interpolate the values for the estimation of the concentration of the protein in my samples. After selecting the interpolate option, a parameters window is open, where I select the 4 parameter logistic regression.
I hope this can help you.
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I am trying to formulate a research title. Seeking expert advice.
(1) What could be the popular area of doing research in the field of Logistics Education, Port performance, Last Mile delivery, Block Chain?
(2) Any suggestion for the possible research gap in these areas?
(3) Any specific title you like to suggest?
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Currently digital transformation in these areas is a hot topic and it can link parts of your fields (see, e.g., ). Moreover, digital twins are a recent research topic in these fields and there are quite a few developments. Developing a serious game supporting digital transformation might be a possible focus and the titel should possibly start with the word integration or similar. The development of integrated mathematical models to improve / solve problems in ports is a nice topic with various research gaps.
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I need a dataset based on blockchain and logistics supply chain
to help me in my PhD thesis
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Certainly! 📦🔗 Here's a digital treasure hunt: explore academic databases like IEEE Xplore, ACM Digital Library, and arXiv for "Blockchain in Logistics" gems. Unearth data diamonds to fuel your PhD quest. Happy hunting! 🚀🔍
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I am planning to study effect on logistics performance/efficiency with provision of private freight terminals and private slidings in Nepal, currently where ICD and ICP are owned by govermnment alone. I couldn't find sufficient papers for review though, and i am looking for help from the community.
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  • I would suggest you check these papers out to and see; ISSN 1366-5545, ISSN 2772-3909, ISSN 2666-822X
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R4TLI 2023 extended abstract submission site is open.
Extended Abstract Submission Deadline – 30th April 2023
The Sri Lanka Society of Transport and Logistics (SLSTL) is organizing the 8th International Conference on Research for Transport and Logistics Industry (R4TLI) 2023, which is scheduled to be held on the 26th of August 2023 in Colombo, Sri Lanka both onsite and virtually.
R4TLI is an initiative that endeavors to promote Research and Development in the Transport and Logistics Industry in Sri Lanka, and in the Asian region helping diagnose its current issues, experienced by the industry and identify potential improvements and sustainable solutions, based on scientific evidence. This annual research conference intends to build a platform for effective dialogue among academics and professionals in the fields, and for showcasing of research outputs and dissemination of new knowledge developed in this regard.
We encourage all of you, academics and professionals interested in the research and development of the transport and logistics industry to join us by submitting Extended Abstracts (the extended abstracts template is attached herewith) on your authentic research, in view of presenting them at the conference and subsequently publishing them in the R4TLI Proceedings. (For past proceedings visit “PUBLICATIONS” menu at www.slstl.lk)
The selected Extended Abstracts will be invited to submit the full paper for the Journal of South Asian Logistics and Transport (JSALT) which is a peer-reviewed fully open-access Journal of the Sri Lanka Society of Transport and Logistics, Moratuwa, Sri Lanka and published by SLJOL (https://jsalt.sljol.info/)
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Please give more detailed information about the conference, the conditions for participation in it.
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How shipping and logistics industry can be improved using Data science and Statistical analysis methods?
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Here are some ways in which these technologies can be leveraged to improve the efficiency and effectiveness of the industry:
  1. Route Optimization: Data science can analyze historical shipping data, traffic patterns, weather conditions, and other relevant factors to optimize shipping routes. This can reduce transit times, fuel consumption, and overall costs while improving delivery reliability.
  2. Demand Forecasting: By utilizing statistical analysis methods, logistics companies can accurately forecast demand for their services. This enables them to plan their resources and capacity effectively, avoiding overstocking or understocking inventory.
  3. Real-time Tracking and Visibility: Data science can facilitate real-time tracking of shipments, providing better visibility to logistics managers and customers. This can lead to more accurate delivery estimates, enhanced customer service, and the ability to proactively address potential delays or issues.
  4. Predictive Maintenance: Applying data science techniques to monitor equipment and vehicles can help identify potential maintenance issues before they lead to breakdowns. This predictive maintenance approach minimizes downtime, reduces repair costs, and improves overall fleet efficiency.
  5. Warehouse Optimization: Statistical analysis can optimize warehouse layouts, inventory management, and order picking processes. By analyzing historical data, logistics companies can identify trends and patterns, leading to better storage decisions and streamlined operations.
  6. Risk Management: Data science can be used to assess and mitigate risks associated with shipping and logistics, such as accidents, theft, or natural disasters. Predictive modeling can help identify high-risk areas and develop strategies to reduce potential losses.
  7. Last-Mile Delivery Efficiency: Data science can optimize last-mile delivery routes by considering various factors, including traffic conditions, customer locations, and delivery preferences. This can result in reduced delivery times and improved customer satisfaction.
  8. Cost Optimization: Through statistical analysis of shipping data and associated costs, logistics companies can identify areas for cost reduction and operational improvements. Data-driven decision-making can lead to significant savings across the supply chain.
  9. Supply Chain Optimization: Data science can analyze the entire supply chain, identifying bottlenecks and inefficiencies. By optimizing the supply chain through data-driven insights, companies can reduce lead times, inventory levels, and transportation costs.
  10. Environmental Impact Reduction: Data science can aid in minimizing the environmental impact of shipping and logistics operations by optimizing routes to reduce carbon emissions, adopting more fuel-efficient transportation options, and implementing sustainable practices.
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What are the skills required in logistics field in Africa?
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The logistics industry in Africa requires a diverse set of skills to effectively navigate the unique challenges and opportunities. Some of the key skills required in the logistics in Africa include:
1. Supply Chain Management: Understanding the end-to-end supply chain, including procurement, transportation, warehousing, and distribution, is essential. Proficiency in managing inventory, demand forecasting, and optimizing logistics processes is crucial.
2. International Trade and Customs: Given the international nature of logistics, knowledge of trade regulations, customs procedures, and import/export documentation is vital. Understanding trade agreements, tariffs, and compliance requirements facilitates smooth cross-border operations.
3. Transportation and Fleet Management: Efficient transportation is critical in Africa, considering the diverse infrastructure and geographical challenges. Proficiency in managing different modes of transportation, optimizing routes, and maintaining an effective fleet is necessary.
4. Warehousing and Inventory Management: Skills in warehouse operations, space utilization, inventory control, and order fulfillment are important for effective logistics management. Knowledge of warehouse layout, storage systems, and inventory tracking methods helps streamline operations.
5. Information Technology and Systems: Proficiency in using logistics management software, transportation management systems (TMS), warehouse management systems (WMS), and enterprise resource planning (ERP) systems is essential. Data analysis, reporting, and leveraging technology for process optimization are crucial skills.
6. Negotiation and Relationship Management: Building strong relationships with suppliers, customers, freight forwarders, and other logistics partners is crucial. Negotiation skills, effective communication, and the ability to collaborate across different stakeholders are important for successful logistics operations.
7. Problem-solving and Decision-making: The logistics field often involves unforeseen challenges and requires the ability to think critically, make quick decisions, and solve problems effectively. Adapting to changing situations and finding innovative solutions is important.
8. Cultural Awareness and Adaptability: Africa is a diverse continent with various cultures, languages, and business practices. Having cultural sensitivity, adaptability, and the ability to work in cross-cultural environments is valuable.
9. Financial Management: Understanding cost analysis, budgeting, and financial management principles is essential to optimize logistics operations and ensure profitability.
10. Environmental and Sustainability Awareness: Recognizing the importance of sustainability and environmental considerations in logistics is becoming increasingly important. Knowledge of sustainable practices, green logistics, and circular economy principles can be advantageous.
These skills provide a foundation for success in the logistics not only in Africa but also other parts of the world. However, it's important to note that the specific skill requirements may vary depending on the industry, sector, and job role within logistics. Continuous learning, staying updated with industry trends, and adapting to the evolving logistics landscape are also crucial for professional growth in this field.
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How to define a quantum circuit of the quantum baker map scrambling? I read the articles based on quantum baker map scrambling : (1) Quantum image encryption based on baker map and 2D logistic map. (2) Quantum image scrambling algorithm based on discrete baker map. In these articles they mentioned the circuit but how did they get it? Anyone, please help me to tackle this issue?
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Designing a quantum circuit for the quantum baker map scrambling involves several steps. Firstly, you need to understand the mathematical description of the discrete baker map and its quantum analog. Then, you can define the necessary quantum gates and operations required to implement the map. This typically involves using qubit rotations, controlled operations, and ancillary qubits. The specific circuit design may vary depending on the details mentioned in the articles you referenced. To tackle this issue, it is recommended to carefully study the articles, analyze the circuit diagrams provided, and comprehend the transformations applied in each step. Additionally, consulting with experts in the field or reaching out to the authors of the articles for clarification can also be helpful in understanding and replicating the circuit design.
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Hello everyone, please I am a masters student of international Logistics and operation management and currently starting my dissertation, I will like To get dissertation topic on SAP. Can anyone assist me on dissertations topics related? Can I also get data on this topic? My supervisors wants me to write something unique and standout from all other students.
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Dear Joy: Try exploring these
Evaluating the Impact of SAP Implementation on Supply Chain Performance: A Comparative Analysis of Companies in Different Industries"
Optimizing Warehouse Management through SAP Integration: A Case Study of [Company/Organization]
Leveraging SAP Analytics for Demand Forecasting and Planning in Global Supply Chains
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Currently, the RGPPM technique is being focused on measuring the carbon footprint during the delivery of merchandise in last-mile logistics. However, it is important to establish KPIs related to the carbon footprint for carrying out comparisons with current methodologies or techniques in industry or academia.
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There are several methodologies and techniques that can be used to measure the carbon footprint of last-mile logistics. Here are a few examples:
1. Emission Factors: This approach is based on using emission factors that are published for different modes of transportation, such as delivery vans or bicycles. Emission factors are used to estimate the amount of CO2 emissions based on the distance travelled and the mode of transportation used.
2. Life Cycle Assessment (LCA): LCA is a technique that evaluates the environmental impact of a product or service throughout its entire life cycle, from raw material extraction to disposal. LCA can be used to identify the carbon footprint of last-mile logistics by considering the emissions associated with the production, distribution, use, and end-of-life of the vehicles and equipment used for delivery.
3. GPS Tracking: GPS tracking technology can be used to track the routes and distances travelled by delivery vehicles. This data can be combined with emission factors to estimate the amount of CO2 emissions generated during the last-mile delivery process.
4. Simulation Models: Simulation models can be used to estimate the carbon footprint of last-mile logistics by simulating the delivery process and estimating the energy consumption and emissions associated with each step.
5. Carbon Accounting Tools: There are a number of carbon accounting tools available that can be used to estimate the carbon footprint of last-mile logistics. These tools use data inputs such as distance, mode of transportation, and fuel consumption to calculate the carbon emissions associated with last-mile delivery.
Overall, the choice of methodology or technique will depend on the specific context and data availability. It may be necessary to use a combination of approaches to obtain a comprehensive and accurate estimate of the carbon footprint of last-mile logistics.
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Using ELISA, we generated standard curve in 4-parameter logistics (4PL).
I wonder if standard curve is consistent in each experiment (drug stability test using ELISA) .
Are there any acceptance criteria or robustness of "standard curve" for this?
I don't think that consistent value is calculated only by R^2>0.95.
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As SSt criteria for 4-parameter logistic curve it is worth to define at least:
- curve depth (the difference between uper and lower asymptote) or equivalent parameter;
- slope for middle part of the curve or equivelent parameter.
It is suggested not to be too strict in establishing the criteria as ELISA is hardly reproducible method.
For further information please refer to:
T.A. Little and D.S. Harding, “Establishing Systems Suitability and Validity Criteria for Analytical Methods and Bioassays,” Bio/Pharma Outsourcing Innovation 2022, Supplement to Pharmaceutical Technology (February 2022).
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With greater emphasis being placed on ‘re-use’ and ‘recycle’,how will future supply chains manage the need to incorporate ‘reverse flows’ and ‘circular logistics’?
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@all Incorporating ‘reverse flows’ and ‘circular logistics’ in supply chains will become increasingly important in the future as businesses strive to minimize waste and reduce their environmental impact. One way to manage the need for these practices is through the use of innovative technologies and systems, such as blockchain and IoT devices, to track and trace products and materials throughout the supply chain. This can help to ensure that waste is properly sorted and recycled, and that products are repurposed or reused where possible.
In addition, businesses can collaborate with suppliers, customers, and other stakeholders to implement closed-loop systems that facilitate the return of used products or materials back into the supply chain. This can involve designing products for disassembly and reuse, or implementing take-back programs that allow customers to return products for recycling or repurposing.
Overall, the key to managing the need for ‘reverse flows’ and ‘circular logistics’ in supply chains is to adopt a holistic approach that considers the entire lifecycle of products and materials. This can help to create a more sustainable and resilient supply chain that benefits both businesses and the environment.
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Please help me with any sops, published literature or any readers manual regarding logistics and resources required to set up a TDM unit.
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There are some resources and logistics that may be required:
1. Equipment: A laboratory equipped with the necessary instruments and reagents for drug analysis.
2. Trained personnel: Skilled professionals such as pharmacists, clinical chemists, and laboratory technicians who are trained in therapeutic drug monitoring.
3. Quality control measures: Standard operating procedures (SOPs) for sample collection, handling, storage, and analysis to ensure accuracy and precision of results.
4. Accreditation: Accreditation from regulatory bodies such as the Clinical Laboratory Improvement Amendments (CLIA) or the College of American Pathologists (CAP) may be required.
5. Information technology infrastructure: A laboratory information management system (LIMS) to manage patient data and test results.
6. Collaboration with healthcare providers: Collaboration with physicians or other healthcare providers who can order tests and interpret results is essential.
7. Financial resources: Funding for equipment, personnel salaries, quality control measures, accreditation fees, and other expenses associated with setting up a therapeutic drug monitoring service.
8. Legal considerations: Compliance with local regulations regarding laboratory testing and patient privacy laws is crucial.
9. Marketing strategy: Developing a marketing strategy to promote the service to potential clients such as hospitals or clinics may also be necessary.
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I would like to get the information regarding real data on transportation. How can I get that particular data.
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There are several ways to obtain real data on transportation:
1. Government websites: Many government agencies collect and publish data on transportation, such as the U.S. Department of Transportation or the European Union's Eurostat. These websites often provide access to datasets, reports, and other resources related to transportation.
2. Private companies: Some private companies collect and sell transportation data, such as INRIX or TomTom. These companies may offer access to real-time traffic information, travel times, and other data related to transportation.
3. Research institutions: Universities and research institutions often conduct studies on transportation-related topics and publish their findings in academic journals or reports. These publications may include data on traffic patterns, public transit usage, and other aspects of transportation.
4. Open data portals: Many cities and countries have open data portals that provide access to a wide range of datasets, including those related to transportation. Examples include New York City's Open Data Portal or the UK's Data.gov.uk.
5. Surveys: Surveys can be conducted by government agencies or private organizations to gather information about travel behavior, commuting patterns, and other aspects of transportation. These surveys may be available online or in-person through phone interviews or mail surveys.
Overall, there are many sources of real data on transportation available for researchers, policymakers, and others interested in this.
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Hello,
I am modeling bacterial growth using a logistic growth function:
X' = μX(1-N/κ),
where B' is the increment in bacterial population, μ the specific growth rate, N the total bacterial density, and κ the carrying capacity.
I would like to use the Gompertz model, instead, but I am not sure if I can use the parameters of the logistic model. The parameters for the Gompertz are:
L(t) = AᴮCexp(-e(-B(t-M)))
where:
L(t) is the log of the number of bacteria at time ‘t’ (in hour);
A is the asymptotic log of number of bacteria as ‘t’ decreases indefinitely;
C is the asymptotic amount of growth (log number) that occurs as ‘t’ increases indefinitely;
M is the time (in hour) at which the absolute growth rate is at maximum;
and B is the relative growth at time ‘M’.
What parameters of the logistic can I use in the Gompertz model? Is A = κ, for instance?
Thank you
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Just put your data in this software and you will get the Gompertz parameters:
Let me know if you need assistance.
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I need information about Amazon logistics
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Field of Operation: Amazon is an American multinational technology company that specializes in e-commerce, digital streaming, cloud computing, and artificial intelligence. It is one of the world's largest online retailers, offering a wide range of products and services to customers worldwide. In addition to its core retail operations, Amazon also operates subsidiaries such as Amazon Web Services (AWS), Amazon Studios, and Amazon Robotics.
Transportation System: Amazon operates a highly efficient and sophisticated transportation system to support its e-commerce operations. The company uses a combination of in-house and third-party logistics providers to handle the movement of goods from its fulfillment centers to customers around the world. Amazon's transportation network includes a vast fleet of delivery vans, trucks, and planes, as well as partnerships with major shipping carriers such as UPS, FedEx, and the United States Postal Service.
Trade Conditions: As a major player in global e-commerce, Amazon operates in a highly competitive and complex trade environment. The company is subject to various regulations and trade agreements that govern cross-border trade, including tariffs, customs duties, and import/export regulations. Amazon has also faced criticism and regulatory scrutiny over issues such as labor practices, privacy concerns, and antitrust violations. Additionally, the company has been impacted by the COVID-19 pandemic and related disruptions to global supply chains and logistics networks.
I hope this information helps with your documentation. Let me know if you need any further assistance.
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The equation dx/dt = F(x) can be linearized using Calerman techniques and solved with linear state equation method. But for some condition I found a proper decomposition of F(x) relating to know logist solution od a foundamental canonical problem .
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Hello from 2016 up today i have finally solved any non linear autonomous first orde diff equations . The solution is in terms of important analysical recursion which i will present in a later paper. Regards.
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Dear Statisticians,
I was running binary logistics and this is the output report I get it. The confidence interval looks unusual and I do not understand the meaning of it. Could you help me interpret please? kINDLY refer the file attached for reference.
Have a great days ahead.
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Your extremely high values induce much numerical error. Consider dividing your observables by some scale factor to bring them close to the magnitude of 1, and then repeat your statistical analysis on those normalized observables.
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Dear Colleagues,
Thanks for your prompt responses. But if we plot bifurcation diagram, lypanuov exponent and tragectory plot for function rx(2-3x) it shows different behaviour. So, it attracted my attention to do work on it. The bifurcation diagram of rx(2-3x) suggests that there is no bifurcation but only a little discrete chaos has rate of convergence good as compared with logistic map. If anyone interested in doing work on this new scheme, please send me the email through which we can communicate and whatsapp number also, so that frequency of interaction shall be increased and neck to neck traversing of results can be made jointly.
Manish
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Use two-parameter family in this case as: 2rx(1-1.5x), replace 1.5 by another parameter. You can do iterations like this:
or
I hope that it will help.
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We are well familiar with Logistic Map rx(1-x) but can anyone has the idea about rx(2-3x) map or rx(3-2x). If anyone has the study of these mappings, please familiarise me with that study and if previously in the literature this study does not exists, please help me to study this phenomenon also.
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Dear Colleagues,
Thanks for your prompt responses. But if we plot bifurcation diagram, lypanuov exponent and tragectory plot for function rx(2-3x) it shows different behaviour. So, it attracted my attention to do work on it. The bifurcation diagram of rx(2-3x) suggests that there is no bifurcation but only a little discrete chaos has rate of convergence good as compared with logistic map. If anyone interested in doing work on this new scheme, please send me the email through which we can communicate and whatsapp number also, so that frequency of interaction shall be increased and neck to neck traversing of results can be made jointly.
Manish
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Can anyone help me discuss how logistics in developing countries are going now
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Logistics is a very broad subject, as it determines the entire flow of goods. Many developing countries, yet, do not have a full net of distribution, as many business have grow more recently (when compared to developed countries).
The infrastructure to deliver goods with reliability and on-time is specially important on today's scenario where most of materials are planned just in time for optimization of capital usage.
Areas that face higher or uncertain lead times will have to mobilize more cash to keep the operation running and might end-up not being competitive/ on top of that poor logistic infrasctrucutres might be more expensive by itself and business that require more certainty on their production might end up expending more initial CAPEX to make sure suppliers are nearby.
You might read some more on this calculation on:
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What are some of the accessible yet trustworthy sources of secondary data in the field of logistics and supply chain management?
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There are several sources of secondary data in the field of logistics and supply chain management that are both accessible and trustworthy. Some examples include:
  1. Government agencies: Many government agencies, such as the United States Census Bureau and the United States Department of Transportation, collect and publish data related to logistics and supply chain management.
  2. Professional organizations: Professional organizations, such as the Council of Supply Chain Management Professionals (CSCMP) and the Institute for Supply Management (ISM), often publish reports and data on logistics and supply chain management trends and benchmarks.
  3. Industry associations: Industry associations, such as the National Retail Federation (NRF) and the National Association of Manufacturers (NAM), often publish data and reports on logistics and supply chain management issues that are specific to their industries.
  4. Market research firms: Market research firms, such as Gartner and Forrester, often publish reports and data on logistics and supply chain management trends and issues.
  5. Academic journals: Many academic journals, such as the Journal of Business Logistics and the Journal of Management, publish research on logistics and supply chain management topics.
It's important to carefully evaluate the credibility and reliability of any secondary data sources you use to ensure that the data is accurate and relevant to your research needs.
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can anyone please suggest matlab code for lyapunov exponent of logistic map
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sample Matlab code
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I wish to do a thesis on Service level on last mile logistics during covid. Which analysis tools i could use and why . I wish to investigate the reason behind rising costs.
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I think the answer would be many. As one of the respondent mention, cost benefit analysis is the one. In my opinion it would be good to give additional information on the nature and types of data you have collected? The analysis may depend on this. with my guess, you can apply regression analysis, TOBIT Probit analysis, logistic regression analysis, if at all you have huge data, why not ANN fitting.
Regards.
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I am attempting to perform a coIP after co-culturing cells and need to perform reversible crosslinking. I was thinking of using DSP and DTT to perform the reversible crosslinking. Has anyone performed this type of crosslinking on the two different cell lines? Trying to figure out the logistics on how to add the crosslinking reagent to both cells lines in their preferred growing conditions as the DSP cannot be added into the media.
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It is possible to perform reversible crosslinking using DSP (disuccinimidyl suberate) and DTT (dithiothreitol) on two different cell lines that have been co-cultured. However, there are a few challenges and considerations to keep in mind when using these reagents in this context.
One challenge is that DSP cannot be added directly to the growth media, as it can react with other components in the media and interfere with cell growth. Therefore, it will be necessary to remove the cells from the growth media and add the DSP to the cells in a separate solution. This can be done by gently washing the cells with a solution containing DSP, allowing the DSP to react with the cells for a specified amount of time, and then washing the cells again to remove any unbound DSP.
Another challenge is that DTT can inactivate DSP, so it will be necessary to add DTT to the cells after the DSP has been allowed to react. This can be done by washing the cells with a solution containing DTT, allowing the DTT to react with the cells for a specified amount of time, and then washing the cells again to remove any unbound DTT.
Overall, while it is possible to perform reversible crosslinking using DSP and DTT on co-cultured cells, it will be necessary to carefully consider the logistics of adding these reagents to the cells in their preferred growing conditions. It may also be helpful to consult with other researchers who have experience with this type of crosslinking to obtain guidance and advice.
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Hi How to test Heteroskedasticity and autocorrelation in Logistic Panel Regression?
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Why would you expect that it would be any different than than any other linear statistical model. Best wishes David Booth
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I am trying to identify the three strongest environments in the world for simulation and system dynamics in Operations, logistics and/or Supply chain management - can anyone suggest some environments?
With strong, I mean that have research groups, graduate trainings on the method and UTD-list scientific publications that applies it.
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One of the strongest for mentioned areas might be MIT Sloan System Dynamics Group:
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Like what is the impact factor of Cleaner Logistics and Supply Chain Journal ? Its publisher is Elsevier.
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Since the publisher is Elsevier, I highly doubt that these journals would not post their impact factor if they had any. Guessing from Cleaner Logistics, they are just too new (barely a year old) to compute an Impact Factor for them.
Please have a look at this Elsevier journal homepage to see where the impact factor would be: https://www.sciencedirect.com/journal/journal-of-power-sources
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I am finding it difficult to operationalize/ define last-mile logistics. As far as I understand there are several last-mile fulfilment options (conventional shopping, locker station etc.).
I believe last mile distribution encompasses last-mile delivery, and last mile fulfilment. How does last-mile logistics differ from these concepts?
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In early literature in humanitarian literature it was labeled as the 5 Bs, Body, Bucks, Boxes, Bytes, and Brains. When we talk about last mile it is the most volatile part of the chain and requires special consideration like routing and locating warehouses with barrier consideration which I did my thesis on.
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The SARS-CoV-2 (Covid-19) coronavirus pandemic has, in some respects, through interrupted chains of international supply and supply logistics, reduced the scale of economic globalisation processes. On the other hand, the need for the development of remote Internet communication has increased due to the introduction of home quarantine periods and lockdowns imposed on selected sectors of the economy in 2020. Consequently, the scale of internetisation and digitalisation of various aspects of business conducted by companies and enterprises has increased. As a result of the growth of the Internet, the importance of information globalisation has increased in terms of remote Internet-based communication. In a multi-year perspective, the importance of environmental and pro-climate globalisation may increase in the future. In view of the above, how else will globalisation processes change in this decade of the 21st century? Will the current energy crisis, the unfolding food crisis, the migration crisis
What is your opinion on this?
What is your opinion on this topic?
Please reply,
I invite you all to discuss,
Thank you very much,
Best regards,
Dariusz Prokopowicz
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Over the past decades, a number of sources of globalization have emerged. One of them is technological progress, which has led to a sharp reduction in transport and communication costs, a significant reduction the costs of processing, storing and using information.
The second source of globalization is trade liberalization and other forms of economic liberalization that have curtailed protectionist policies and made world trade freer. As a result there were tariffs have been substantially reduced, and many other barriers to trade in goods and services have been removed. Other liberalization measures have led to an increase in the movement of capital and other factors of production.
The third source of globalization can be considered a significant expansion of the scope of organizations, which became possible both as a result of technological progress and wider horizons of management on basis of new means of communication. Thus, many companies that previously focused only on local markets have expanded their production and marketing capabilities, reaching the national, multinational, international and even global level.
Globalization brings not only benefits, it is fraught with negative consequences or potential problems, which some of its critics see as a great danger.
One of the main problems is related to the question: who benefits from globalization? In fact, most of the benefits are rich countries or individuals. The unfair distribution of the benefits of globalization gives rise to the threat of conflicts at the regional, national and international levels.
The second problem is related to potential regional or global instability due to the interdependence of national economies at the global level. Local economic fluctuations or crises in one country may have regional or even global implications.
The third set of problems posed by globalization is caused by the fear that control over the economies of individual countries may shift from sovereign governments to other hands, including the most powerful states, multinational or global corporations and international organizations.
Because of this, some see globalization as an attempt to undermine national sovereignty. For this reason, globalization can make national leaders feel helpless before its forces, and the electorate - antipathy towards her. Such sentiments can easily turn into extreme nationalism and xenophobia with calls for protectionism, lead to the growth of extremist political movements, which is potentially fraught with serious conflicts.
The problem generated by globalization - the infringement of national sovereignty and the independence of political leaders - can also be largely resolved on the basis of international cooperation, for example, by a clear delineation of the powers of the parties, i.e. national governments and their leaders, on the one hand, and international organizations and multinational or global corporations, on the other. The very involvement of political leaders in building the necessary institutions to deal with these and other globalization-related issues will help them regain the sense that they are in control of their future and in control of their positions in the world.
Globalized world. In the meantime, unfortunately, the world is moving in the opposite direction, along the path of political and military dictate of a strong
weak, that in the context of globalization of all aspects of the life of the world community, it is fraught with a global confrontation.
The current crisis of the Western economy is not a recession because it is not cyclical and is not limited to 12-16 months. What is happening in the US and Europe today is a structural crisis, a process that began in the fourth quarter of 2021 and will continue for at least five years without interruption. However, the West does not understand the causes and essence of the crisis, because they do not have theories describing it. That is why, according to the economist, the American and European authorities are doing stupid things instead of effective measures to resolve problems.
It was impossible to avoid this crisis, because they went too far. They have expanded private consumption so much that they can no longer keep it. You need to name the main number. There is an indicator in the United States that they do not disclose in public discussion: this is the level of price growth for all industrial goods, not only for final goods entering the wholesale trade, but in general for everything, from raw materials to the final product. For the first time, the rise in prices for manufactured goods exceeded the level of the late 1970s. The previous peak was at the end of 1947. There are 23 with something percent.
The entire system of socio-political management in the West, both in the USA and in Europe, is built through representatives of the middle class, qualified consumers. Today this instrument is being destroyed. Instead of the middle class, new poor people appear, who have a middle-class attitude, but they have no money.
The sanctions pressure on Russia has exacerbated the economic problems of the West. European financiers note that EU politicians are afraid to take responsibility for decisions taken under the slogans of transatlantic solidarity and assistance to Ukraine.
In fact, this whole situation with global confrontation and the breakdown of the dollar system is disastrous for the United States not by economic factors, but by intellectual ones. Roughly speaking, Washington will undoubtedly lose to Moscow only because the US does not even have a concept of a plan to solve the colossal economic problems and save the dollar system.
Intellectual life in the US and Russia goes in opposite directions. The US has nothing left for a long time. There, no one can imagine even a weak positive scenario. The complete absence of any thought, not to mention the concept.
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Have any survey about a logistics differentiation in a supply chain context?
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I am trying to identify the three strongest environments in the world for simulation and system dynamics in Operations, logistics and/or Supply chain management - can anyone suggest some environments?
With strong, I mean that have research groups, graduate trainings on the method and UTD-list scientific publications that applies it.
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I going to suggest 2 resources for you. The first is. One of Goldratt's disciples. The second is the management science group at Michigan State University. Both have done excellent work in this area.. The screenshot shows Dr Choe's location. Best wishes David Booth
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What do you think are the key factors that could trigger a food crisis in your country in the next quarters and/or years?
Due to many different factors, a food crisis can develop in many countries. The international supply and supply logistics chains that were interrupted during the SARS-CoV-2 (Covid-19) coronavirus pandemic have not been fully rebuilt. Rising fuel prices are driving up the cost of transporting food products to shops. The decline in fertiliser production is also driving up the cost of producing crops. In addition, the war in Ukraine has resulted in a decline in cereal supplies to many countries. The lack of electricity has caused a decline in the production of nitrogenous fertilisers. This then caused a decrease in the production of CO2, which benefits producers of many types of food products. Many food product factories are raising the prices of their products due to increases in raw material, energy and fuel prices. Many production facilities are reducing the scale of production. There may be job cuts. Consumption is falling due to high inflation. If a downturn in the economy occurs in the next quarters, many companies may go out of business and unemployment will rise. In addition, periods of increasingly severe drought, more and more hot days and less and less rain and more and more frequent fires in many parts of the world are causing a significant drop in crop production in agriculture. On the other hand, further food crises may arise in the future in the long term, which will be the result of a global climate crisis developing on a multi-year scale.
In view of the above, I address the following question to the esteemed community of researchers and scientists:
What do you think are the key factors that could trigger a food crisis in your country in the next quarters and/or years?
What should be done to reduce the scale of development of the food crisis?
What is your opinion on the subject?
What do you think about this topic?
Please reply,
I invite you all to discuss,
Thank you very much,
Regards,
Dariusz Prokopowicz
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Dear Dariusz
I dare to assert that all epigenetic factors may initiate a food crisis (Social interaction, war, disease, financial, created deficiencies etc.) More important is to have strategies to contain an emerging problem so that it will not spread globally. To avoid that we formed the UNO. In the post war era we also created the global market. Unfortunately, this is an economic concept that is based on competition and the winner in competition are those with with power. Now we are witnessing the global economy is dividing and consolidating in blocks. Unfortunately, the blocksformation is permananentl restructured and driven by a few war mongers. For them power is more important than food for the global citizen.
Many people are afraid and believe that we have too many people on the globe. For them war is the preferred mode to assure access to food. They cant imagine that with innovation and new circulatory technologies it is possible to multiply food supply. Food shortage is always a distribution problem. There are many actors around that increase value through shortage. The alternative is entrepreneurial collaboration with advanced technologies to assure a very large diversity of healthy food, enhanced with free global trade via internet. Science has failed to convince taxpayer that with sustainable technologies we will always have enough food for everybody.
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I am looking for journals with no APC in the field of transport and logistics.
Please give some recommendations
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I have found that a journal called "Transportation Reviews" state on their website no submission or publication fees. I have also found a journal called "Transportation" from the publisher recommended by Nolberto Munier - charges are not mentioned specifically on the website but seems to be implied that there are no charges - suggest you email them if you want to confirm with certainty. Another one, also clearly stated no submission or publication fees; International Journal of Logistics Research and Management.
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Can anyone kindly share the details of the procedure or software or link of it for analyzing critical crop weed competition from the two sets of weedy and weed-free situations in a cropped field
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I don't know if you still need an answer, but you might try this software:
If you could share some real data that I can use for teaching purposes, I can do it for you.
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2 Logistic chaotic sequences generation, we are generating two y sequence(Y1,Y2) to encrypt a data
2D logistic chaotic sequence, we are generating x and y sequence to encrypt a data
whether the above statement is correct, kindly help in this and kindly share the relevant paper if possible
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after reading an article baesd on quantum image encryption I think these two chaotic sequences are used for a key generation, not for encryption.
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I have two curves, the first one is a growth curve of a microorganisms reported as cells/mL, whereas the second one is the concentration (as % of the initial concentration) of a specific compound.
I'm trying to understand if there is any correlation between the 2 curves (hence I want to know if the reduction of the compound is depended on the microorganisms growth) but I'm not sure which solution is the best. I tried Pearson correlation but I'm not sure it's the best method since the curves are not linear but they have both a logistic type curve.
I've attached an excel file where I reported an example of the data.
Thanks for your help
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1st : Please see the Excel attachment for 7 steps for doing the cubic plot.
2nd : About t- and F- distribution statistics and p-values that come from Excel Regression Analysis (which you "... couldn't find the functions to obtain those data on my excel ..."):
google-search for
"Why is Data Analysis not showing in Excel?"
... as soon as you add-it-in ... "the Data Analysis ToolPak"
then look for / google
"excel data analysis toolpak regression"
Good Luck
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Will drones evolve as a parcel delivery model or as objects of intelligent logistics networks meaning that they will deliver to distribution centers not to final users?
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May be helpful for your work:
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I have 186 respondents who were participated in my study. My questionnaire is dichotomous double bounded and asked their willingness to pay for the conservation programme.
To examine the determinants towards willingness to pay, I need to run the regression analysis but still not clear to use either logistic or probit regression.
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Less than sample size of 500, its better to run chi square of variables association.
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Respected Researchers and Academics,
I am recently working on a research proposal entitled "𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐜 𝐈𝐝𝐞𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 (𝐀𝐈𝐒) 𝐃𝐚𝐭𝐚 𝐟𝐨𝐫 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐝 𝐌𝐚𝐫𝐢𝐭𝐢𝐦𝐞 𝐓𝐫𝐚𝐧𝐬𝐩𝐨𝐫𝐭 𝐚𝐧𝐝 𝐋𝐨𝐠𝐢𝐬𝐭𝐢𝐜𝐬 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧" in which I plan to apply different econometrics and operations research tools to model the AIS-driven big data for efficient maritime transport and logistics decision.
The Automatic Identification Systems (AIS) provides high frequency, real-time positioning and sailing patterns for almost the whole world’s commercial fleet of international voyages with a gross tonnage above 300 and all passenger ships equipped with an AIS transmitter. The information in the AIS message includes vessel identity (IMO No., MMSI, vessel name, and type), physical appearance (length overall, beam), voyage related information (draught, destination, estimated time of arrival), and dynamic data (speed, course, rate of turn, etc.). Currently, the stated information from AIS can be found in different AIS-related commercial databases (For instance; Marine Traffic, Spire, AXS Marine, exactEarth, Signal Ocean).
AIS data in predicting maritime traffic and waterway patterns, caution area traffic prediction, vessel trajectory prediction, naval sensors, etc. have been widely used in many studies which are mainly in 𝐎𝐜𝐞𝐚𝐧 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 nature. However, I am mostly interested to explore the 𝐌𝐚𝐫𝐢𝐭𝐢𝐦𝐞 𝐓𝐫𝐚𝐧𝐬𝐩𝐨𝐫𝐭 𝐚𝐧𝐝 𝐋𝐨𝐠𝐢𝐬𝐭𝐢𝐜𝐬 aspects based on AIS data.
I will be grateful if you kindly help me in identifying probable research gaps considering the aforesaid discussion.
Best Regards
Mojahid
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Regionally, the importance of ship calls/deviations that are not on the main route in the economy of local ports can be explained. For example, deviations made by a ship going from China to Germany outside its main route can be sorted out with AIS and the added value it provides to the mooring areas can be demonstrated.
Of course, this is a computable process with secondary data as well. However, a relationship should be established between the number of AIS deviations and development.
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I have thought to cover the challenges faced by various functions in managing the supply chain - Procurement, Quality Assurance, Technical, Logistics , Planning and Regulatory
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I have an article on how JLR utilised digital training to upskill staff during the pandemic. You could use this for your literature review i.e. looking at how other manufacturing businesses have utilised digital technology during the pandemic to come up with solutions to challenges thrown at us due to the pandemic.
Not specifically related to suppliers but maybe of some use.
Best Regards
Martin
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Dear talented researchers,
I want to calculate three solar irradiance components (DNI, DHI, & GHI) from these equations which contain logistics, maximum and minimum, Less than, Greater or equal, terms.
How can I use these equations please? I don not know how to use equations 12 & 13 because they have terms such as max, min.
I am not sure, but it seems to be a Logistic map.
1- just for example, how to solve this part from equation 12?
min (1:88 * 10^-8 CO^4, SOLZEN < 77)
2-how to deal with these mathematical operation such as greater than, less than 77, equal or greater than inside these equations?
Thank you very much for your kind response.
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Dear Zhwan
I have been thinking in your problem and I b elieve that the logistic part that bothers you could have the following explanation:
Logistics refers to a curve normally known as a sigmoid (very similar to the letter S,) but with right horizontal lines at both extremes, instead fo the curls, and very used in many disciplines, most especially in Artificial Intelligence, and normally varies between -x and x. It is defined as tanh and equal to the ratio between sinh and cosh.
In my opinion, for your geographical position, you should compute the ratio solzen and solalt , and then multiply it by CO^2, which meaning I don’t remember.
Because the sigmoid, and think that we can safetly take a value of 0.5, since it is the average of the linear part of the curve.
Multiplying 0.5 by CO^2 this product MUST be < 77.
Just tu represent that in MCDM is my problem
Therefore, I would appreciate it if you can give me the following values:
CO
CO^4
SOLZEN
SOLALT
1/SOLZEN tan^2
I believe that with this data I could be able to solve the problem using SIMUS.
I agree with your efforts to use algebra and trigonometry, but how are you going to express the < relationships?
Anyway, let me know if you agree with my suggestion, and if you do, give me the values I request.
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Logistics seeks both to address real-world problems and research questions and to unite terminological, conceptual and methodological research aspects. In the last 20 years, biological research has developed extremely powerful methods and tools for fundamental and applied research. There is furthermore an increasing desire to build integrative research platforms that combine interdisciplinary and multi-level data to the structural complexity of biological systems. How much attention do you give to logistics for your research plans? Do you think logistics supports research methods, innovation, quality, value, and impact as well as training and participation opportunities for students as well as for practitioners? If so how and if not why not.
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Andrew Lewis
- You've made excellent points with clear analogies - thank you! I agree with your synopsis that "Transitioning biological understanding to this next level is certainly in large part a logistical problem" and that we must strive to the "coordination of manpower and computational power resources being put towards the pursuit of understanding things at this level."
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Currently, two distinct types of indicators are being developed: (1) monitoring frameworks based on macro indicators that summarize progress at the national level, and (2) micro indicators aimed at analyzing circularity at the product level.
How to bridge the gap between the macro and micro levels of Circular Economy using any Logistic approach? My focus is to incorporate logistic strategies which could help in bridging the gap between the macro and micro levels of CE. Any reference papers or suggestions will be highly appreciated.
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Scfviscat meso level!
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How should i approach this question
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When you are going to find impact of X ( here company’s logistics performance) on Y ( here global international trade), you need to be able to measure both variable (X and Y) using some tools. To do this you need to read the literature and find the criteria/ measures for global international trade.
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Hi,
I plan to write my thesis on sustainable solutions to reduce carbon emissions in inbound logistics. As a result, I'm looking for articles and was wondering if you have any recommendations.
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The logistics Performance Index (LPI) developed by the World Bank measures the overall logistics performance of a country. On the other hand, the Liner Shipping Connectivity Index (LSCI) determines how well a country is connected to the global shipping networks. Both LPI and LSCI fail to reflect the complete picture of the maritime logistics performance of a country although some of the indicators of LPI and LSCI are significant for measuring maritime logistics performance.
The purpose of the question is to formulate a list of indicators that truly reflect maritime logistic performance.
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Some indicators in LPI and LSCI may be the key to the performance of maritime logistics. I recently read an article titled "The propellants of the Logistics Performance Index: an empirical panel investigation of the European region". The authors examined the factors that influence the LPI. The authors analyzed the factors that influence the LPI. I believe that a similar approach can be used to identify the key factors affecting the LSCI.
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E-commerce has transformed the way we buy things and created jobs for millions of people, among other benefits. However, I have personally observed a significant amount of waste associated with online shopping in the form of unnecessary plastic packaging, a large amount of wrapping to deliver hot meals, and a variety of other things. Delivery is handled by integrated logistic companies in some countries, such as CaiNiao in China. One of the main aims of the logistics industry is to reduce logistic costs in order to keep prices competitive. In that case, how can they be persuaded to adopt sustainable (reusable) packaging and other similar solutions? Please share your ideas for resolving this issue.
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Hot foods ordered have to travel quite some distances, and often take quite some time, especially during evenings, when there could well be huge and long traffic queues, which add delays in delivery. The foods should arrive hot enough to go from the delivery door to a plate on the table. The wrappings should take into account delayed deliveries... so what is your solution?
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Hello! I am currently doing GARP species distribution models. However, I can't find a clear paper about the model's assumptions on what the input data should be or how should they behave.
For example, is it necessary that environmental data are normally distributed? Or that data should follow a certain function (e.g. logistic or linear)?
Thank you for your answers!
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What will be the future applications of analytics of large data sets conducted in the computing cloud on computerized Business Intelligence analytical platforms in Big Data database systems in enterprise logistics management?
The analytics conducted on computerized Business Intelligence platforms is one of the key advanced information technology technologies of the fourth technological revolution, known as Industry 4.0. The current technological revolution described as Industry 4.0 is determined by the development of the following technologies of advanced information processing: Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence, Business Intelligence and other advanced data mining technologies.
The analytics conducted on computerized Business Intelligence platforms currently supports business management processes, including logistics management.
In my opinion, the use of analytics of large data sets conducted in the computing cloud on computerized Business Intelligence analytical platforms in Big Data database systems in enterprise logistics management, including supply logistics, production logistics, provision of services and distribution of manufactured products and services, is currently growing.
The analytics conducted on large data sets conducted in the cloud computing on Business Intelligence computerized platforms in Big Data database systems makes it particularly easy to identify opportunities and threats to business development, allows for quick generation of analytical reports on selected issues in the economic and financial situation of the business entity. In this way, the generated reports can be helpful in the processes of enterprise logistics management, including supply logistics, production logistics, provision of services and distribution of manufactured products and services.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
What will be the future applications of analytics of large data sets conducted in the computing cloud on computerized Business Intelligence analytical platforms in Big Data database systems in enterprise logistics management?
Please reply
I invite you to the discussion
The issues of the use of information contained in Big Data database systems for the purposes of conducting Business Intelligence analyzes are described in the publications:
I invite you to discussion and cooperation.
Best wishes
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It is rising field since intelligence and in general artificial intelligence becomes the dominant technology of current era
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The on-line share of all grocery retail in the UK had been bumping along at around 6% for the last four years, then almost doubled, to just under 12%, at the start of lockdown, and has since fallen back to around 10%. During a recent lecture to MSc students the course participants were divided on the future potential of on-line grocery retail and whether the growth seen during the pandemic is sustainable. Some students thought that, having tried on-line shopping for the first-time during lockdown, they would probably continue using it for bulky and long shelf-life items, but also use local stores for fresh produce (probably the worst possible outcome for the grocery retailers as they would be left with delivering the high logistics cost and low margin products). Other students thought that they would go back to in-store shopping and that the current 10% market share would probably fall back to around 7 or 8%. Most of the analysis I have seen shows that UK grocery retail home delivery charges (anything from £1 to £7 dependent on day, time slot etc) do not begin to cover the costs. This suggests that at some point the grocery retailers will have to start passing on the real costs and/or collaborate to improve efficiencies (shared hubs and last mile delivery fleets?). Interested in any views / research on the topic.
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A low-margin, volume-intensive business selling perishable products that require quick delivery in special temperature-controlled vehicles makes for complex and expensive operations. But Instacart, for one, has reportedly made headway by emphasizing (a) flexibility (i.e., a mix of independent contractors and full-time employees, picking orders directly from stores); (b) shared platform costs (i.e., passing on the cost of development and maintenance for its website to those who use it, which channels more resources into improving the platform than would normally be be feasible); (c) portability (i.e., minimizing fixed infrastructure makes it easier to expand in new markets); and (d) volume (i.e., brand-neutrality helps attract clients from across the grocery world).
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How to introduce a covariate in a multivariable logistic prediction model when the event of interest always occurs in individuals exposed to this covariate. It is possible to determine the adjusted odds ratio with their 95% confidence interval?
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I attach information to exemplify the problem.
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Small open economies face the challenge how to improve logistics system in order to stimulate international trade and national competitiveness.
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In my opinion, the use of ICT and Industry 4.0 information technologies to improve computerized e-logistics systems and increase the automation of logistics processes are factors in the improvement of logistics systems. In addition, shortening of international logistics chains of supply and sourcing and distribution increased its importance during the SARS-CoV-2 (Covid-19) coronavirus pandemic.
Best wishes,
Dariusz Prokopowicz
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What kind of scientific research dominate in the field of Smart production?
Please, provide your suggestions for a question, problem or research thesis in the issues: Smart production.
Please reply.
I invite you to the discussion
Thank you very much
Best wishes
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Dear Dr. Dariuscz Prokopowicz,
I consider that the type of scientific research that dominates in the field of "intelligent production" revolves around theoretical discussions about the existence of "intelligent territories", generating in turn a concept that has been developed recently, taking as bases the notions of:
a) "Knowledge Society"
b) "Knowledge Economy"
c) "Sustainable Development"
d) "Social Inclusion".
These are new types of territorial spaces in which we interact for the sake of a new advance in the Economy and thinking about the New Social Structures that are being generated after Covid-19 with new behaviors of Human Beings.
My respects.
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To support the debate I enclosed the slides of IEOM South America 2021 keynote.
My guess:
The future performance of production and logistics relies on knowledge-intensive technologies, components and systems. The development of this strategic knowledge depends on a close collaboration between industry and academia in research projects and education initiatives.
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Please have look on our(Eminent Biosciences (EMBS)) collaborations.. and let me know if interested to associate with us
Our recent publications In collaborations with industries and academia in India and world wide.
EMBS publication In association with Universidad Tecnológica Metropolitana, Santiago, Chile. Publication Link: https://pubmed.ncbi.nlm.nih.gov/33397265/
EMBS publication In association with Moscow State University , Russia. Publication Link: https://pubmed.ncbi.nlm.nih.gov/32967475/
EMBS publication In association with Icahn Institute of Genomics and Multiscale Biology,, Mount Sinai Health System, Manhattan, NY, USA. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/29199918
EMBS publication In association with University of Missouri, St. Louis, MO, USA. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/30457050
EMBS publication In association with Virginia Commonwealth University, Richmond, Virginia, USA. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/27852211
EMBS publication In association with ICMR- NIN(National Institute of Nutrition), Hyderabad Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/23030611
EMBS publication In association with University of Minnesota Duluth, Duluth MN 55811 USA. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/27852211
EMBS publication In association with University of Yaounde I, PO Box 812, Yaoundé, Cameroon. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/30950335
EMBS publication In association with Federal University of Paraíba, João Pessoa, PB, Brazil. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/30693065
Eminent Biosciences(EMBS) and University of Yaoundé I, Yaoundé, Cameroon. Publication Link: https://pubmed.ncbi.nlm.nih.gov/31210847/
Eminent Biosciences(EMBS) and University of the Basque Country UPV/EHU, 48080, Leioa, Spain. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/27852204
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Eminent Biosciences(EMBS) and NIPER , Hyderabad, India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/29053759
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Eminent Biosciences(EMBS) and Jawaharlal Nehru Technological University, Hyderabad , India. Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/28472910
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Eminent Biosciences(EMBS) and NIPER, Hyderabad, India. ) Publication Link: https://www.ncbi.nlm.nih.gov/pubmed/29053759
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Sincerely,
Dr. Anuraj Nayarisseri
Principal Scientist & Director,
Eminent Biosciences.
Mob :+91 97522 95342
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I am trying to create a qualitative question about logistics system on courier services. Is there any example ?
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